中文摘要：

针对直线超声电机很强的非线性和时变特性，提出了模糊神经网络控制。为了更好地将PID控制的经验融人模糊神经网络，对离散型PID表达式的各项进行了划分，将轨迹跟踪误差信号、轨迹跟踪误差信号的变化和轨迹跟踪误差信号的变化率等三项作为模糊神经网络的输入。采用自适应律并结合了反向传播算法和梯度下降法进行学习优化。试验结果表明，所设计的模糊神经网络控制器不仅明显优于PID和自组织神经网络控制器，而且具有很好的抗干扰能力。

英文摘要：

In view of the strong non-linear and time-varying characteristics of linear ultrasonic motors, put forward a fuzzy recurrent neural network controller. In order to better integrate the experience of the PID con- trol into fuzzy neural network, the discrete PID expression were divided into the tracking error, the change of tracking error and the change rate of tracking error, which input into the fuzzy neural networks. In order to improve the control of the convergence speed and robustness of the proposed controller, the adaptive law and BP algorithm and gradient descent optimization mechanism for learning and accurate optimization were adopt- ed. The results show that the fuzzy recurrent neural network controller is better than PID and self-structuring neural network controller, and has a good anti-interference capability.